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Journal Articles

Classification-Based Fuel Injection Fault Detection of a Trainset Diesel Engine Using Vibration Signature Analysis

Moosa Ayati, Farzad A. Shirazi, Saeed Ansari-Rad, Alireza Zabihihesari

Publisher: ASME

J. Dyn. Sys., Meas., Control. May 2020, 142(5): 051003.

Paper No: DS-18-1046

https://doi.org/10.1115/1.4046270

Published Online: March 3, 2020

View Articletitled, Classification-Based Fuel Injection Fault Detection of a Trainset Diesel Engine Using Vibration Signature Analysis

Topics: Condition monitoring, Diesel engines, Engines, Flaw detection, Fuels, Sensors, Signals, Support vector machines, Vibration, Cylinders

Journal Articles

Performance Comparison Between Fast Fourier Transform-Based Segmentation, Feature Selection, and Fault Identification Algorithm and Neural Network for the Condition Monitoring of Centrifugal Equipment

Samer Gowid, Roger Dixon, Saud Ghani

Publisher: ASME

J. Dyn. Sys., Meas., Control. June 2017, 139(6): 061013.

Paper No: DS-16-1007

https://doi.org/10.1115/1.4035458

Published Online: April 13, 2017

View Articletitled, Performance Comparison Between Fast Fourier Transform-Based Segmentation, Feature Selection, and Fault Identification Algorithm and Neural Network for the Condition Monitoring of Centrifugal Equipment

Topics: Algorithms, Artificial neural networks, Feature selection, Image segmentation, Machinery, Condition monitoring

Journal Articles

A General Approach for Current-Based Condition Monitoring of Induction Motors

W. J. Bradley, M. K. Ebrahimi, M. Ehsani

Publisher: ASME

J. Dyn. Sys., Meas., Control. July 2014, 136(4): 041024.

Paper No: DS-13-1171

https://doi.org/10.1115/1.4026874

Published Online: April 28, 2014

View Articletitled, A General Approach for Current-Based Condition Monitoring of Induction Motors

Topics: Bearings, Condition monitoring, Electromagnetic induction, Engines, Flaw detection, Motors, Rotors, Stators, Algorithms, Stress

Journal Articles

Model-Based Condition Monitoring of an Electro-Hydraulic Valve

Andreas Steinboeck, Wolfgang Kemmetmüller, Christoph Lassl, Andreas Kugi

Publisher: ASME

J. Dyn. Sys., Meas., Control. November 2013, 135(6): 061010.

Paper No: DS-12-1077

https://doi.org/10.1115/1.4024800

Published Online: August 23, 2013

View Articletitled, Model-Based Condition Monitoring of an Electro-Hydraulic Valve

Topics: Condition monitoring, Valves, Wear, Cylinders, Algorithms

Journal Articles

Parameter Identification for a High-Performance Hydrostatic Actuation System Using the Variable Structure Filter Concept

S. R. Habibi, R. Burton

Publisher: ASME

J. Dyn. Sys., Meas., Control. March 2007, 129(2): 229–235.

https://doi.org/10.1115/1.2431816

Published Online: May 24, 2006

View Articletitled, Parameter Identification for a High-Performance Hydrostatic Actuation System Using the Variable Structure Filter Concept

Topics: Actuators, Filters, Hydrostatics, Parameter estimation, State estimation, Maintenance, Condition monitoring, Errors, Nonlinear systems

Journal Articles

A Dynamic Model for Condition Monitoring of a High-Power CO 2 Industrial Laser

J. F. Tu, J. G. Katter, Jr., L. E. Monacelli, M. Gartner

Publisher: ASME

J. Dyn. Sys., Meas., Control. June 1999, 121(2): 157–164.

https://doi.org/10.1115/1.2802448

Published Online: June 1, 1999

View Articletitled, A Dynamic Model for Condition Monitoring of a High-Power CO 2 Industrial Laser

Topics: Carbon dioxide, Condition monitoring, Dynamic models, Lasers, Carbon dioxide lasers, Flow (Dynamics), Laser cooling, Pressure

Journal Articles

Estimation of Gear Backlash: Theory and Simulation

Jeffrey L. Stein, Churn-Hway Wang

Publisher: ASME

J. Dyn. Sys., Meas., Control. March 1998, 120(1): 74–82.

https://doi.org/10.1115/1.2801324

Published Online: March 1, 1998

View Articletitled, Estimation of Gear Backlash: Theory and Simulation

Topics: Gears, Simulation, Algorithms, Servomechanisms, Clearances (Engineering), Computer simulation, Condition monitoring, Machinery, Manufacturing, Momentum

Journal Articles

Multivariable Trend Analysis for System Monitoring Through Self-Organizing Neural Networks

Siyu Zhang, R. Ganesan

Publisher: ASME

J. Dyn. Sys., Meas., Control. June 1997, 119(2): 223–228.

https://doi.org/10.1115/1.2801237

Published Online: June 1, 1997

View Articletitled, Multivariable Trend Analysis for System Monitoring Through Self-Organizing Neural Networks

Topics: Artificial neural networks, Self-organization, System monitoring, Trend analysis, Signals, Vibration, Algorithms, Bearings, Condition monitoring, Flaw detection

Journal Articles

Tool Condition Monitoring in Machining by Fuzzy Neural Networks

S. Li, M. A. Elbestawi

Publisher: ASME

J. Dyn. Sys., Meas., Control. December 1996, 118(4): 665–672.

https://doi.org/10.1115/1.2802341

Published Online: December 1, 1996

View Articletitled, Tool Condition Monitoring in Machining by Fuzzy Neural Networks

Topics: Condition monitoring, Fuzzy neural nets, Machining, Cutting, Wear, Artificial neural networks, Computation, Engines, Feature selection, Feedforward control

Journal Articles

Artificial Neural Network Architecture Design Using Similarity Measure With Applications in Engineering Monitoring and Diagnosis

Yuedong Chen, R. Du

Publisher: ASME

J. Dyn. Sys., Meas., Control. September 1996, 118(3): 635–639.

https://doi.org/10.1115/1.2801194

Published Online: September 1, 1996

View Articletitled, Artificial Neural Network Architecture Design Using Similarity Measure With Applications in Engineering Monitoring and Diagnosis

Topics: Artificial neural networks, Design, Condition monitoring, Cutting, Welding

Journal Articles

A New Sensor for Real-Time Milling Tool Condition Monitoring

C. James Li, S. Y. Li

Publisher: ASME

J. Dyn. Sys., Meas., Control. June 1993, 115(2A): 285–290.

https://doi.org/10.1115/1.2899033

Published Online: June 1, 1993

View Articletitled, A New Sensor for Real-Time Milling Tool Condition Monitoring

Topics: Condition monitoring, Milling, Sensors, Cutting, Wear, Fracture (Materials), Fracture (Process), Algorithms

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Classification-Based Fuel Injection Fault Detection of a Trainset Diesel Engine Using Vibration Signature Analysis

Performance Comparison Between Fast Fourier Transform-Based Segmentation, Feature Selection, and Fault Identification Algorithm and Neural Network for the Condition Monitoring of Centrifugal Equipment

A General Approach for Current-Based Condition Monitoring of Induction Motors

Model-Based Condition Monitoring of an Electro-Hydraulic Valve

Parameter Identification for a High-Performance Hydrostatic Actuation System Using the Variable Structure Filter Concept

A Dynamic Model for Condition Monitoring of a High-Power CO 2 Industrial Laser

Estimation of Gear Backlash: Theory and Simulation

Multivariable Trend Analysis for System Monitoring Through Self-Organizing Neural Networks

Tool Condition Monitoring in Machining by Fuzzy Neural Networks

Artificial Neural Network Architecture Design Using Similarity Measure With Applications in Engineering Monitoring and Diagnosis

A New Sensor for Real-Time Milling Tool Condition Monitoring

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